---
title: "Who cites Da-Cheng Juan — 2,400 papers of our library"
description: "2,400 papers of the Elamur Research library cite the works of Da-Cheng Juan, found in their bibliographies · page 1 of 2 · 1–100; the most cited first."
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---
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# Who cites Da-Cheng Juan

2,416 citations of their works from 2,400 papers of our library (of the 141,840 whose bibliographies we read) · 197 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Da-Cheng Juan](https://md.research.elamur.ai/free/en/authors/da-cheng-juan/)

**1** [2](https://md.research.elamur.ai/free/en/authors/da-cheng-juan/cited-by/page/2/) [next →](https://md.research.elamur.ai/free/en/authors/da-cheng-juan/cited-by/page/2/)

1. [**Survey of Hallucination in Natural Language Generation**Ziwei Ji, Nayeon Lee, Rita Frieske, et al.*2022 · 5,957 citations*](https://md.research.elamur.ai/free/en/papers/ji-2022-survey-hallucination-natural-language-generation/)
2. [**A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,222 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/)
3. [**A Survey of Large Language Models**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,863 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/)
4. [**DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models**Zhihong Shao, Peiyi Wang, Qihao Zhu, et al.*2024 · 2,013 citations*](https://md.research.elamur.ai/free/en/papers/shao-2024-deepseekmath-pushing-limits-mathematical-reasoning/)
5. [**Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context**Gemini Team, Petko Georgiev, Ving Ian Lei, et al.*2024 · 1,522 citations*](https://md.research.elamur.ai/free/en/papers/gemini-team-2024-gemini-1-5-unlocking-multimodal/)
6. [**A Comprehensive Overview of Large Language Models**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,286 citations*](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/)
7. [**Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone**Marah Abdin, Jyoti Aneja, Hany Awadalla, et al.*2024 · 1,113 citations*](https://md.research.elamur.ai/free/en/papers/abdin-2024-phi-3-technical-report-highly/)
8. [**FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation**Sewon Min, Kalpesh Krishna, Xinxi Lyu, et al.*2023 · 971 citations*](https://md.research.elamur.ai/free/en/papers/min-2023-factscore-fine-grained-atomic-evaluation/)
9. [**Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models**Yue Zhang, Yafu Li, Leyang Cui, et al.*2023 · 966 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-siren-s-song-ai-ocean/)
10. [**Qwen2.5-VL Technical Report**Shuai Bai, Keqin Chen, Xuejing Liu, et al.*2025 · 948 citations*](https://md.research.elamur.ai/free/en/papers/bai-2025-qwen2-5-vl-technical/)
11. [**MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI**Xiang Yue, Yuansheng Ni, Kai Zhang, et al.*2023 · 948 citations*](https://md.research.elamur.ai/free/en/papers/yue-2023-mmmu-massive-multi-discipline-multimodal/)
12. [**MMBench: Is Your Multi-modal Model an All-around Player?**Yuan Liu, Haodong Duan, Yuanhan Zhang, et al.*2023 · 907 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-mmbench-multi-modal-model-all/)
13. [**Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution**Peng Wang, Shuai Bai, Sinan Tan, et al.*2024 · 819 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-qwen2-vl-enhancing-vision/)
14. [**SGLang: Efficient Execution of Structured Language Model Programs**Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, et al.*2023 · 710 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-sglang-efficient-execution-structured-language/)
15. [**ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools**Team GLM, Aohan Zeng, Bin Xu, et al.*2024 · 688 citations*](https://md.research.elamur.ai/free/en/papers/glm-2024-chatglm-family-large-language-models/)
16. [**The Flan Collection: Designing Data and Methods for Effective Instruction Tuning**Shayne Longpre, Le Hou, Tu Vu, et al.*2023 · 592 citations*](https://md.research.elamur.ai/free/en/papers/longpre-2023-flan-collection-designing-data-methods/)
17. [**Galactica: A Large Language Model for Science**Ross Taylor, Marcin Kardas, Guillem Cucurull, et al.*2022 · 565 citations*](https://md.research.elamur.ai/free/en/papers/taylor-2022-galactica-large-language-model-science/)
18. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code**Naman Jain, King Han, Alex Gu, et al.*2024 · 540 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/)
19. [**Unleashing the potential of prompt engineering for large language models**Banghao Chen, Zhaofeng Zhang, Nicolas Langrene, et al.*2023 · 536 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-unleashing-potential-prompt-engineering-large/)
20. [**Jailbreaking Black Box Large Language Models in Twenty Queries**Patrick Chao, Alexander Robey, Edgar Dobriban, et al.*2023 · 533 citations*](https://md.research.elamur.ai/free/en/papers/chao-2023-jailbreaking-black-box-large-language/)
21. [**How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites**Zhe Chen, Weiyun Wang, Hao Tian, et al.*2024 · 529 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-far-gpt-4v-closing/)
22. [**Enabling Large Language Models to Generate Text with Citations**Tianyu Gao, Howard Yen, Jiatong Yu, et al.*2023 · 477 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-enabling-large-language-models-generate/)
23. [**OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems**Chaoqun He, Renjie Luo, Yuzhuo Bai, et al.*2024 · 448 citations*](https://md.research.elamur.ai/free/en/papers/he-2024-olympiadbench-challenging-benchmark-promoting-agi/)
24. [**FinGPT: Open-Source Financial Large Language Models**Hongyang Yang, Xiao-Yang Liu, Christina Dan Wang*2023 · 445 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-fingpt-open-source-financial-large/)
25. [**MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts**Pan Lu, Hritik Bansal, Tony Xia, et al.*2023 · 441 citations*](https://md.research.elamur.ai/free/en/papers/lu-2023-mathvista-evaluating-mathematical-reasoning-foundation/)
26. [**LLaVA-OneVision: Easy Visual Task Transfer**Bo Li, Yuanhan Zhang, Dong Guo, et al.*2024 · 440 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llava-onevision-easy-visual-task/)
27. [**Kimi k1.5: Scaling Reinforcement Learning with LLMs**Kimi Team, Angang Du, Bofei Gao, et al.*2025 · 413 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-k1-5-scaling-reinforcement/)
28. [**BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains**Yanis Labrak, Adrien Bazoge, Emmanuel Morin, et al.*2024 · 408 citations*](https://md.research.elamur.ai/free/en/papers/labrak-2024-biomistral-collection-open-source-pretrained/)
29. [**Yi: Open Foundation Models by 01.AI**Alex Young, Bei Chen, Chao Li, et al.*2024 · 402 citations*](https://md.research.elamur.ai/free/en/papers/ai-2024-yi-open-foundation-models-01/)
30. [**Large Language Models Cannot Self-Correct Reasoning Yet**Jie Huang, Xinyun Chen, Swaroop Mishra, et al.*2023 · 396 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-large-language-models-cannot-self/)
31. [**VILA: On Pre-training for Visual Language Models**Ji Lin, Hongxu Yin, Wei Ping, et al.*2023 · 368 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-vila-pre-training-visual-language/)
32. [**WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct**Haipeng Luo, Qingfeng Sun, Can Xu, et al.*2023 · 366 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-wizardmath-empowering-mathematical-reasoning-large/)
33. [**The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery**Chris Lu, Cong Lu, Robert Tjarko Lange, et al.*2024 · 362 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-ai-scientist-fully-automated/)
34. [**HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models**Tianrui Guan, Fuxiao Liu, Xiyang Wu, et al.*2023 · 326 citations*](https://md.research.elamur.ai/free/en/papers/guan-2023-hallusionbench-advanced-diagnostic-suite-entangled/)
35. [**MM-LLMs: Recent Advances in MultiModal Large Language Models**Duzhen Zhang, Yahan Yu, Jiahua Dong, et al.*2024 · 318 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-mm-llms-recent-advances-multimodal/)
36. [**CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing**Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.*2023 · 315 citations*](https://md.research.elamur.ai/free/en/papers/gou-2023-critic-large-language-models-self/)
37. [**HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal**Mantas Mazeika, Long Phan, Xuwang Yin, et al.*2024 · 312 citations*](https://md.research.elamur.ai/free/en/papers/mazeika-2024-harmbench-standardized-evaluation-framework-automated/)
38. [**Chain-of-Verification Reduces Hallucination in Large Language Models**Shehzaad Dhuliawala, Mojtaba Komeili, Jing Xu, et al.*2023 · 299 citations*](https://md.research.elamur.ai/free/en/papers/dhuliawala-2023-chain-verification-reduces-hallucination-large/)
39. [**OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models**Yuliang Liu, Zhang Li, Mingxin Huang, et al.*2023 · 297 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-ocrbench-hidden-mystery-ocr-large/)
40. [**Evaluating Verifiability in Generative Search Engines**Nelson Liu, Tianyi Zhang, Percy Liang*2023 · 294 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-evaluating-verifiability-generative-search-engines/)
41. [**A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future Directions**Junchao Wu, Shu Yang, Runzhe Zhan, et al.*2025 · 276 citations*](https://md.research.elamur.ai/free/en/papers/wu-2025-survey-llm-generated-text-detection/)
42. [**An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language Models**Liang Chen, Haozhe Zhao, Tianyu Liu, et al.*2024 · 276 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-image-worth-1-2-tokens/)
43. [**Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling**Zhe Chen, Weiyun Wang, Yue Cao, et al.*2024 · 276 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-expanding-performance-boundaries-open/)
44. [**Are We on the Right Way for Evaluating Large Vision-Language Models?**Lin Chen, Jinsong Li, Xiaoyi Dong, et al.*2024 · 263 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-right-way-evaluating-large-vision/)
45. [**GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models**Iman Mirzadeh, Keivan Alizadeh, Hooman Shahrokhi, et al.*2024 · 262 citations*](https://md.research.elamur.ai/free/en/papers/mirzadeh-2024-gsm-symbolic-understanding-limitations-mathematical/)
46. [**The Effect of Sampling Temperature on Problem Solving in Large Language Models**Matthew Renze*2024 · 262 citations*](https://md.research.elamur.ai/free/en/papers/renze-2024-effect-sampling-temperature-problem-solving/)
47. [**DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines**Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, et al.*2023 · 261 citations*](https://md.research.elamur.ai/free/en/papers/khattab-2023-dspy-compiling-declarative-language-model/)
48. [**Large Language Models for Data Annotation and Synthesis: A Survey**Zhen Tan, Dawei Li, Song Wang, et al.*2024 · 259 citations*](https://md.research.elamur.ai/free/en/papers/tan-2024-large-language-models-data-annotation/)
49. [**MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies**Shengding Hu, Yuge Tu, Xu Han, et al.*2024 · 258 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-minicpm-unveiling-potential-small-language/)
50. [**A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models**S.M Towhidul Islam Tonmoy, S M Mehedi Zaman, Vinija Jain, et al.*2024 · 246 citations*](https://md.research.elamur.ai/free/en/papers/tonmoy-2024-comprehensive-survey-hallucination-mitigation-techniques/)
51. [**InternVideo2: Scaling Foundation Models for Multimodal Video Understanding**Yi Wang, Kunchang Li, Xinhao Li, et al.*2024 · 239 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-internvideo2-scaling-foundation-models/)
52. [**Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey**Zeyu Han, Chao Gao, Jinyang Liu, et al.*2024 · 236 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-parameter-efficient-fine-tuning-large/)
53. [**MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?**Renrui Zhang, Dongzhi Jiang, Yichi Zhang, et al.*2024 · 231 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-mathverse-multi-modal-llm-truly/)
54. [**OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments**Tianbao Xie, Danyang Zhang, Jixuan Chen, et al.*2024 · 228 citations*](https://md.research.elamur.ai/free/en/papers/xie-2024-osworld-benchmarking-multimodal-agents-open/)
55. [**A Survey of Hallucination in Large Foundation Models**Vipula Rawte, Amit Sheth, Amitava Das*2023 · 222 citations*](https://md.research.elamur.ai/free/en/papers/rawte-2023-survey-hallucination-large-foundation-models/)
56. [**NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models**Chankyu Lee, Rajarshi Roy, Mengyao Xu, et al.*2024 · 219 citations*](https://md.research.elamur.ai/free/en/papers/lee-2024-nv-embed-improved-techniques-training/)
57. [**Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models**Mosh Levy, Alon Jacoby, Yoav Goldberg*2024 · 212 citations*](https://md.research.elamur.ai/free/en/papers/levy-2024-same-task-more-tokens-impact/)
58. [**Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP**Omar Khattab, Keshav Santhanam, Xiang Lisa Li, et al.*2022 · 211 citations*](https://md.research.elamur.ai/free/en/papers/khattab-2022-demonstrate-search-predict-composing-retrieval/)
59. [**RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models**Cheng Niu, Yuanhao Wu, Juno Zhu, et al.*2024 · 204 citations*](https://md.research.elamur.ai/free/en/papers/niu-2024-ragtruth-hallucination-corpus-developing-trustworthy/)
60. [**DeepSeek-VL: Towards Real-World Vision-Language Understanding**Haoyu Lu, Wen Liu, Bo Zhang, et al.*2024 · 201 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-deepseek-vl-real-world/)
61. [**Measuring Multimodal Mathematical Reasoning with MATH-Vision Dataset**Ke Wang, Junting Pan, Weikang Shi, et al.*2024 · 198 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-measuring-multimodal-mathematical-reasoning-math/)
62. [**ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search**Dan Zhang, Sining Zhoubian, Ziniu Hu, et al.*2024 · 197 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-rest-mcts-llm-self-training/)
63. [**InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models**Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.*2025 · 195 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-internvl3-exploring-advanced-training/)
64. [**What matters when building vision-language models?**Hugo Laurençon, Leo Tronchon, Matthieu Cord, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2024-matters-building-vision-language-models/)
65. [**LLM in a flash: Efficient Large Language Model Inference with Limited Memory**Keivan Alizadeh, Seyed Iman Mirzadeh, Dmitry Belenko, et al.*2024 · 192 citations*](https://md.research.elamur.ai/free/en/papers/alizadeh-2024-llm-flash-efficient-large-language/)
66. [**From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline**Tianle Li, Wei-Lin Chiang, Evan Frick, et al.*2024 · 191 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-crowdsourced-data-high-quality-benchmarks/)
67. [**OpenHands: An Open Platform for AI Software Developers as Generalist Agents**Xingyao Wang, Boxuan Li, Yufan Song, et al.*2024 · 190 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-openhands-open-platform-ai/)
68. [**The Prompt Report: A Systematic Survey of Prompt Engineering Techniques**Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.*2024 · 187 citations*](https://md.research.elamur.ai/free/en/papers/schulhoff-2024-prompt-report-systematic-survey-prompt/)
69. [**Towards Building Multilingual Language Model for Medicine**Pengcheng Qiu, Chaoyi Wu, Xiaoman Zhang, et al.*2024 · 183 citations*](https://md.research.elamur.ai/free/en/papers/qiu-2024-towards-building-multilingual-language-model/)
70. [**Aya Expanse: Combining Research Breakthroughs for a New Multilingual Frontier**John Dang, Shivalika Singh, Daniel D'souza, et al.*2024 · 180 citations*](https://md.research.elamur.ai/free/en/papers/dang-2024-aya-expanse-combining-research-breakthroughs/)
71. [**Knowledge Conflicts for LLMs: A Survey**Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.*2024 · 179 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-knowledge-conflicts-llms-survey/)
72. [**Findings of the WMT24 General Machine Translation Shared Task: The LLM Era Is Here but MT Is Not Solved Yet**Tom Kocmi, Eleftherios Avramidis, Rachel Bawden, et al.*2024 · 177 citations*](https://md.research.elamur.ai/free/en/papers/kocmi-2024-findings-wmt24-general-machine-translation/)
73. [**Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization**Yu-Min Tseng, Yu-Chao Huang, Teng-Yun Hsiao, et al.*2024 · 177 citations*](https://md.research.elamur.ai/free/en/papers/tseng-2024-two-tales-persona-llms-survey/)
74. [**Aya 23: Open Weight Releases to Further Multilingual Progress**Viraat Aryabumi, John Dang, Dwarak Talupuru, et al.*2024 · 171 citations*](https://md.research.elamur.ai/free/en/papers/aryabumi-2024-aya-23-open-weight-releases/)
75. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 170 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/)
76. [**WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models**Hongliang He, Wenlin Yao, Kaixin Ma, et al.*2024 · 168 citations*](https://md.research.elamur.ai/free/en/papers/he-2024-webvoyager-building-end-end-web/)
77. [**Generative Representational Instruction Tuning**Niklas Muennighoff, Hongjin Su, Liang Wang, et al.*2024 · 165 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2024-generative-representational-instruction-tuning/)
78. [**Long-form factuality in large language models**Jerry Wei, Chengrun Yang, Xinying Song, et al.*2024 · 162 citations*](https://md.research.elamur.ai/free/en/papers/wei-2024-long-form-factuality-large-language/)
79. [**InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency**Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.*2025 · 159 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-internvl3-5-advancing-open/)
80. [**MiniCheck: Efficient Fact-Checking of LLMs on Grounding Documents**Liyan Tang, Philippe Laban, Greg Durrett*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/tang-2024-minicheck-efficient-fact-checking-llms/)
81. [**When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs**Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/kamoi-2024-when-can-llms-actually-correct/)
82. [**FacTool: Factuality Detection in Generative AI — A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios**I-Chun Chern, Steffi Chern, Shiqi Chen, et al.*2023 · 158 citations*](https://md.research.elamur.ai/free/en/papers/chern-2023-factool-factuality-detection-generative-ai/)
83. [**GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models**Aohan Zeng, Xin Lv, Qinkai Zheng, et al.*2025 · 157 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-4-glm-4-5-agentic/)
84. [**VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks**Jing Yu Koh, Robert Lo, Lawrence Jang, et al.*2024 · 156 citations*](https://md.research.elamur.ai/free/en/papers/koh-2024-visualwebarena-evaluating-multimodal-agents-realistic/)
85. [**Moshi: a speech-text foundation model for real-time dialogue**Alexandre Defossez, Laurent Mazare, Manu Orsini, et al.*2024 · 154 citations*](https://md.research.elamur.ai/free/en/papers/defossez-2024-moshi-speech-text-foundation-model/)
86. [**BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages**Junho Myung, Nayeon Lee, Yi Zhou, et al.*2024 · 147 citations*](https://md.research.elamur.ai/free/en/papers/myung-2024-blend-benchmark-llms-everyday-knowledge/)
87. [**Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs**Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.*2025 · 145 citations*](https://md.research.elamur.ai/free/en/papers/microsoft-2025-phi-4-mini-technical-report/)
88. [**Generative Verifiers: Reward Modeling as Next-Token Prediction**Lunjun Zhang, Arian Hosseini, Hritik Bansal, et al.*2024 · 143 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-generative-verifiers-reward-modeling-as/)
89. [**Automatically Correcting Large Language Models: Surveying the Landscape of Diverse Automated Correction Strategies**Liangming Pan, Michael Saxon, Wenda Xu, et al.*2024 · 140 citations*](https://md.research.elamur.ai/free/en/papers/pan-2024-automatically-correcting-large-language-models/)
90. [**Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models**Bernd Bohnet, Vinh Q. Tran, Pat Verga, et al.*2022 · 136 citations*](https://md.research.elamur.ai/free/en/papers/bohnet-2022-attributed-question-answering-evaluation-modeling/)
91. [**Many-Shot In-Context Learning**Rishabh Agarwal, Avi Singh, Lei M. Zhang, et al.*2024 · 134 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2024-many-shot-context-learning/)
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